Cycling Signatures: Identifying Cycling Motions in Time Series using Algebraic Topology
Recurrence is a fundamental characteristic of dynamical systems with complicated behavior. Understanding the inner structure of recurrence is challenging, especially if the system has many degrees of freedom and is subject to noise. We develop algebraic topological notions for identifying and classi...
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Main Authors | , , , |
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Format | Journal Article |
Language | English |
Published |
07.12.2023
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Subjects | |
Online Access | Get full text |
DOI | 10.48550/arxiv.2312.04734 |
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Summary: | Recurrence is a fundamental characteristic of dynamical systems with
complicated behavior. Understanding the inner structure of recurrence is
challenging, especially if the system has many degrees of freedom and is
subject to noise. We develop algebraic topological notions for identifying and
classifying elementary recurrent motions -- called cycling -- and the
transitions between those. Statistics on these cycling motions can be computed
from sampled trajectories (time series data), providing coarse global
information on the structure of the recurrent behavior. We demonstrate this
through three examples; in particular, we identify and analyze six cycling
motions in a four dimensional system with a hyperchaotic attractor. We see this
as a promising approach to reveal coarse-grained dynamical information on
high-dimensional systems. |
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DOI: | 10.48550/arxiv.2312.04734 |